PHM Paper with Code

PHM Paper with Code

• A novel deep learning approach for intelligent fault diagnosis applications based on time-frequency images | SpringerLink
  • Code: ozggultekin/MultisensoryDataFusionWithSTFT
  • Dataset: Konstruktions- und Antriebstechnik (KAt)  -  Data Sets and Download (Universität Paderborn)
• A Hybrid Method for Condition Monitoring and Fault Diagnosis of Rolling Bearings With Low System Delay
  • Code: Western-OC2-Lab/Vibration-Based-Fault-Diagnosis
• Logistic-ELM: A Novel Fault Diagnosis Method for Rolling Bearings
  • Code: TAN-OpenLab/logistic-ELM
• Deep Convolutional Networks in System Identification
  • Code: antonior92/sysid-neuralnet
• Generalized multiscale feature extraction for remaining useful life prediction of bearings with generative adversarial networks
  • Code: opensuh/GMFE
• TFN: An Interpretable Neural Network with Time-Frequency Transform Embedded for Intelligent Fault Diagnosis
  • Code: ChenQian0618/TFN not yet available
• Applications of Unsupervised Deep Transfer Learning to Intelligent Fault Diagnosis: A Survey and Comparative Study
  • Code: ZhaoZhibin/UDTL
• Self-Supervised Learning for Data Scarcity in a Fatigue Damage Prognostic Problem
• Forecasting remaining useful life: Interpretable deep learning approach via variational Bayesian inferences
• Temporal Convolutional Memory Networks for Remaining Useful Life Estimation of Industrial Machinery
• A Neural Network-Evolutionary Computational Framework for Remaining Useful Life Estimation of Mechanical Systems
• A Comparative Study between Bayesian and Frequentist Neural Networks for Remaining Useful Life Estimation in Condition-Based Maintenance
• Crafting Adversarial Examples for Deep Learning Based Prognostics (Extended Version)
• False Data Injection Attacks in Internet of Things and Deep Learning enabled Predictive Analytics
• Multi-Sensor Prognostics using an Unsupervised Health Index based on LSTM Encoder-Decoder

References